# Knowledge Discovery by Accuracy Maximization

## Documentation for package ‘KODAMA’ version 1.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

categorical_table | Categorical Information
clinical | Clinical Data of a Cohort of Prostate Cancer Patiens
continuous_table | Continuous Information
core_cpp | Maximization of Cross-Validateed Accuracy Methods
dinisurface | Ulisse Dini Data Set Generator
floyd | Find Shortest Paths Between All Nodes in a Graph
frequency_matching | Frequency Matching
helicoid | Helicoid Data Set Generator
k.test | K-Test of Statistical Association
knn.double.cv | Cross-Validation with k-Nearest Neighbors algorithm.
knn.kodama | k-Nearest Neighbors Classifier.
KODAMA | Knowledge Discovery by Accuracy Maximization
loads | Variable Ranking
lymphoma | Lymphoma Gene Expression Dataset
mcplot | Evaluation of the Monte Carlo accuracy results
MetRef | Nuclear Magnetic Resonance Spectra of Urine Samples
normalization | Normalization Methods
pca | Principal Components Analysis
pls.double.cv | Cross-Validation with PLS-DA.
pls.kodama | Partial Least Squares regression.
scaling | Scaling Methods
spirals | Spirals Data Set Generator
swissroll | Swiss Roll Data Set Generator
transformy | Conversion Classification Vector to Matrix
txtsummary | Median and Coefficient Interval
USA | State of the Union Data Set